The present exemplary embodiment relates to Lean Document Production (LDP) for excess capacity in dynamic production and manufacturing. It finds particular application in conjunction with document printing operations and will be described with particular reference thereto. However, it is to be appreciated that the present exemplary embodiment is also amenable to other applications.
Conventional print shops are organized in a manner that is functionally independent of the print jobs, the print job mix, and the total volume of print jobs passing through the system. The conventional print shops operate in a dynamic environment in which the set of production jobs is neither fixed nor has known a priori. The print shops have the flexibility to accept or reject certain print jobs, in order to maximize revenue or minimize operational costs. Operators of print shops often need to know what level of excess capacity their shops have in order to decide whether the print shop can handle additional jobs, and if so how many. The print shops traditionally measure the level of excess capacity for the shop in terms of the utilization levels of individual equipment. For example, in a document production environment, excess capacity is expressed as a printer A being busy X % of the time or inserter B being Y % utilized.
While utilizing the excess capacity of individual machines requires an array of innovations to make document production a “lean” process, the concept of cellular manufacturing remains at the heart of this technology, and this has created a number of technical challenges, the most notable of which is how to measure and utilize excess capacity of an entire print shop efficiently in a manufacturing environment that is organized around the notion of cells. The implication of this is that if the excess capacity of a piece of equipment such as a printer is measured without regard to the excess capacity of other equipment used for the same print job, then one would effectively create a gap between the excess capacity levels of different (types of) machines that must be closely involved in order to complete a single or multiple manufacturing jobs. Besides the emergence of measuring and utilizing excess capacity of an entire print shop, there are a number of other issues that pose additional challenges to operators employed in LDP systems.
One issue is that since most print jobs require using more than one type or piece of equipment at different times during the printing process, it is unclear how the utilization level of an individual piece of equipment can be combined to capture the utilization level of the print shop as a whole.
Another area where issues exist is that since print jobs have non-uniform or sporadic arrival times and due dates, in most cases the excess capacity of the print shop is irregular and non-static. The excess capacity may fluctuate depending on the time of day or day of the month. In general, the excess capacity is lower during peak production times than during off-peak times.
An additional issue is that variance of jobs in a job mix. This refers to the fact that print jobs (especially the ones found in large print shops) vary significantly in sizes, arrival times, and due dates, such that the equipment required for each job can no longer be sufficiently characterized by any “textbook” distribution pattern (such as normal or exponential distributions) that has a finite variance. For example, as the percentage of long jobs versus short jobs changes, a print shop may exhibit higher or lower levels of excess capacity. Given that many scheduling algorithms and systems do not take into account the effect of job sizes, arrival times, and due dates on the overall capacity of a print shop, new schedulers are needed to meet this challenge. To address these shortcomings and give the shop operator a global view of excess capacity, the present application presents a system and method that effectively aggregates the idle capacity of the production equipment to compute the shop-level excess capacity.